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Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging
BACKGROUND: Health behaviors such as physical inactivity, unhealthy eating, smoking tobacco, and alcohol use are leading risk factors for noncommunicable chronic diseases and play a central role in limiting health and life satisfaction. To date, however, health behaviors tend to be considered separa...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8235290/ https://www.ncbi.nlm.nih.gov/pubmed/34114962 http://dx.doi.org/10.2196/24887 |
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author | van Allen, Zack Bacon, Simon L Bernard, Paquito Brown, Heather Desroches, Sophie Kastner, Monika Lavoie, Kim Marques, Marta McCleary, Nicola Straus, Sharon Taljaard, Monica Thavorn, Kednapa Tomasone, Jennifer R Presseau, Justin |
author_facet | van Allen, Zack Bacon, Simon L Bernard, Paquito Brown, Heather Desroches, Sophie Kastner, Monika Lavoie, Kim Marques, Marta McCleary, Nicola Straus, Sharon Taljaard, Monica Thavorn, Kednapa Tomasone, Jennifer R Presseau, Justin |
author_sort | van Allen, Zack |
collection | PubMed |
description | BACKGROUND: Health behaviors such as physical inactivity, unhealthy eating, smoking tobacco, and alcohol use are leading risk factors for noncommunicable chronic diseases and play a central role in limiting health and life satisfaction. To date, however, health behaviors tend to be considered separately from one another, resulting in guidelines and interventions for healthy aging siloed by specific behaviors and often focused only on a given health behavior without considering the co-occurrence of family, social, work, and other behaviors of everyday life. OBJECTIVE: The aim of this study is to understand how behaviors cluster and how such clusters are associated with physical and mental health, life satisfaction, and health care utilization may provide opportunities to leverage this co-occurrence to develop and evaluate interventions to promote multiple health behavior changes. METHODS: Using cross-sectional baseline data from the Canadian Longitudinal Study on Aging, we will perform a predefined set of exploratory and hypothesis-generating analyses to examine the co-occurrence of health and everyday life behaviors. We will use agglomerative hierarchical cluster analysis to cluster individuals based on their behavioral tendencies. Multinomial logistic regression will then be used to model the relationships between clusters and demographic indicators, health care utilization, and general health and life satisfaction, and assess whether sex and age moderate these relationships. In addition, we will conduct network community detection analysis using the clique percolation algorithm to detect overlapping communities of behaviors based on the strength of relationships between variables. RESULTS: Baseline data for the Canadian Longitudinal Study on Aging were collected from 51,338 participants aged between 45 and 85 years. Data were collected between 2010 and 2015. Secondary data analysis for this project was approved by the Ottawa Health Science Network Research Ethics Board (protocol ID #20190506-01H). CONCLUSIONS: This study will help to inform the development of interventions tailored to subpopulations of adults (eg, physically inactive smokers) defined by the multiple behaviors that describe their everyday life experiences. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24887 |
format | Online Article Text |
id | pubmed-8235290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-82352902021-07-02 Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging van Allen, Zack Bacon, Simon L Bernard, Paquito Brown, Heather Desroches, Sophie Kastner, Monika Lavoie, Kim Marques, Marta McCleary, Nicola Straus, Sharon Taljaard, Monica Thavorn, Kednapa Tomasone, Jennifer R Presseau, Justin JMIR Res Protoc Proposal BACKGROUND: Health behaviors such as physical inactivity, unhealthy eating, smoking tobacco, and alcohol use are leading risk factors for noncommunicable chronic diseases and play a central role in limiting health and life satisfaction. To date, however, health behaviors tend to be considered separately from one another, resulting in guidelines and interventions for healthy aging siloed by specific behaviors and often focused only on a given health behavior without considering the co-occurrence of family, social, work, and other behaviors of everyday life. OBJECTIVE: The aim of this study is to understand how behaviors cluster and how such clusters are associated with physical and mental health, life satisfaction, and health care utilization may provide opportunities to leverage this co-occurrence to develop and evaluate interventions to promote multiple health behavior changes. METHODS: Using cross-sectional baseline data from the Canadian Longitudinal Study on Aging, we will perform a predefined set of exploratory and hypothesis-generating analyses to examine the co-occurrence of health and everyday life behaviors. We will use agglomerative hierarchical cluster analysis to cluster individuals based on their behavioral tendencies. Multinomial logistic regression will then be used to model the relationships between clusters and demographic indicators, health care utilization, and general health and life satisfaction, and assess whether sex and age moderate these relationships. In addition, we will conduct network community detection analysis using the clique percolation algorithm to detect overlapping communities of behaviors based on the strength of relationships between variables. RESULTS: Baseline data for the Canadian Longitudinal Study on Aging were collected from 51,338 participants aged between 45 and 85 years. Data were collected between 2010 and 2015. Secondary data analysis for this project was approved by the Ottawa Health Science Network Research Ethics Board (protocol ID #20190506-01H). CONCLUSIONS: This study will help to inform the development of interventions tailored to subpopulations of adults (eg, physically inactive smokers) defined by the multiple behaviors that describe their everyday life experiences. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24887 JMIR Publications 2021-06-11 /pmc/articles/PMC8235290/ /pubmed/34114962 http://dx.doi.org/10.2196/24887 Text en ©Zack van Allen, Simon L Bacon, Paquito Bernard, Heather Brown, Sophie Desroches, Monika Kastner, Kim Lavoie, Marta Marques, Nicola McCleary, Sharon Straus, Monica Taljaard, Kednapa Thavorn, Jennifer R Tomasone, Justin Presseau. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 11.06.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included. |
spellingShingle | Proposal van Allen, Zack Bacon, Simon L Bernard, Paquito Brown, Heather Desroches, Sophie Kastner, Monika Lavoie, Kim Marques, Marta McCleary, Nicola Straus, Sharon Taljaard, Monica Thavorn, Kednapa Tomasone, Jennifer R Presseau, Justin Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging |
title | Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging |
title_full | Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging |
title_fullStr | Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging |
title_full_unstemmed | Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging |
title_short | Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging |
title_sort | clustering of unhealthy behaviors: protocol for a multiple behavior analysis of data from the canadian longitudinal study on aging |
topic | Proposal |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8235290/ https://www.ncbi.nlm.nih.gov/pubmed/34114962 http://dx.doi.org/10.2196/24887 |
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